K. V. Subrahmanyam

405 total citations
20 papers, 200 citations indexed

About

K. V. Subrahmanyam is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Mathematical Physics. According to data from OpenAlex, K. V. Subrahmanyam has authored 20 papers receiving a total of 200 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 6 papers in Computational Theory and Mathematics and 4 papers in Mathematical Physics. Recurrent topics in K. V. Subrahmanyam's work include Complexity and Algorithms in Graphs (5 papers), Advanced Algebra and Geometry (3 papers) and Advanced Graph Theory Research (3 papers). K. V. Subrahmanyam is often cited by papers focused on Complexity and Algorithms in Graphs (5 papers), Advanced Algebra and Geometry (3 papers) and Advanced Graph Theory Research (3 papers). K. V. Subrahmanyam collaborates with scholars based in India, Australia and Germany. K. V. Subrahmanyam's co-authors include Geok Soon Hong, Gábor Ivanyos, Youming Qiao, Jianfei Dong, Yoke San Wong, A.R. Mohanty, Sanjeev Saluja, Wong Yoke San, Sheng Huang and Jaikumar Radhakrishnan and has published in prestigious journals such as The International Journal of Advanced Manufacturing Technology, Journal of Computer and System Sciences and Lecture notes in computer science.

In The Last Decade

K. V. Subrahmanyam

15 papers receiving 185 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
K. V. Subrahmanyam India 6 80 69 64 38 37 20 200
C. Sueur France 8 65 0.8× 45 0.7× 45 0.7× 10 0.3× 20 0.5× 42 363
Sri R. Kolla United States 8 38 0.5× 73 1.1× 45 0.7× 5 0.1× 17 0.5× 37 274
E. Christen United States 6 15 0.2× 182 2.6× 67 1.0× 41 1.1× 9 0.2× 14 274
G. Golo Netherlands 8 49 0.6× 23 0.3× 45 0.7× 22 0.6× 3 0.1× 20 419
Helfried Peyrl Switzerland 10 15 0.2× 99 1.4× 56 0.9× 6 0.2× 8 0.2× 18 257
Zhewen Shi China 7 10 0.1× 42 0.6× 50 0.8× 14 0.4× 122 3.3× 9 205
Michael Axtell United States 8 13 0.2× 22 0.3× 18 0.3× 11 0.3× 17 0.5× 20 391
Srinath R. Naidu Netherlands 8 34 0.4× 226 3.3× 18 0.3× 6 0.2× 73 2.0× 19 369

Countries citing papers authored by K. V. Subrahmanyam

Since Specialization
Citations

This map shows the geographic impact of K. V. Subrahmanyam's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by K. V. Subrahmanyam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K. V. Subrahmanyam more than expected).

Fields of papers citing papers by K. V. Subrahmanyam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K. V. Subrahmanyam. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by K. V. Subrahmanyam. The network helps show where K. V. Subrahmanyam may publish in the future.

Co-authorship network of co-authors of K. V. Subrahmanyam

This figure shows the co-authorship network connecting the top 25 collaborators of K. V. Subrahmanyam. A scholar is included among the top collaborators of K. V. Subrahmanyam based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with K. V. Subrahmanyam. K. V. Subrahmanyam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Subrahmanyam, K. V., et al.. (2021). A Novel Method for Rainfall Prediction and Classification using Neural Networks. International Journal of Advanced Computer Science and Applications. 12(7). 3 indexed citations
2.
Deshpande, Amit, et al.. (2020). Invariance vs. Robustness Trade-Off in Neural Networks. 1 indexed citations
3.
Deshpande, Amit, et al.. (2019). Universal Adversarial Attack Using Very Few Test Examples. 1 indexed citations
4.
Ivanyos, Gábor, Youming Qiao, & K. V. Subrahmanyam. (2018). Constructive non-commutative rank computation is in deterministic polynomial time. Computational Complexity. 27(4). 561–593. 25 indexed citations
5.
Subrahmanyam, K. V., et al.. (2018). RELATING TENSOR STRUCTURES ON REPRESENTATIONS OF GENERAL LINEAR AND SYMMETRIC GROUPS. Transformation Groups. 23(2). 437–461.
6.
Ivanyos, Gábor, Youming Qiao, & K. V. Subrahmanyam. (2016). Non-commutative Edmonds’ problem and matrix semi-invariants. Computational Complexity. 26(3). 717–763. 24 indexed citations
7.
Rao, U. Mohan, Yog Raj Sood, R. K. Jarial, & K. V. Subrahmanyam. (2015). Preliminary studies on thermal ageing of alternate dielectric liquids for transformers. 48. 1–5. 5 indexed citations
8.
Subrahmanyam, K. V., et al.. (2012). RSK bases and Kazhdan-Lusztig cells. Annales de l’institut Fourier. 62(2). 525–569. 2 indexed citations
9.
Subrahmanyam, K. V., et al.. (2009). KRS bases for rings of invariants and for endomorphism spaces of irreducible modules. arXiv (Cornell University). 1 indexed citations
10.
Subrahmanyam, K. V., Wong Yoke San, Geok Soon Hong, & Sheng Huang. (2009). Cutting force prediction for ball nose milling of inclined surface. The International Journal of Advanced Manufacturing Technology. 48(1-4). 23–32. 29 indexed citations
11.
Subrahmanyam, K. V., et al.. (2008). A geometric approach to the Kronecker problem I: The two row case. Proceedings - Mathematical Sciences. 118(2). 213–226. 3 indexed citations
12.
Dong, Jianfei, K. V. Subrahmanyam, Yoke San Wong, Geok Soon Hong, & A.R. Mohanty. (2005). Bayesian-inference-based neural networks for tool wear estimation. The International Journal of Advanced Manufacturing Technology. 30(9-10). 797–807. 61 indexed citations
13.
Balaji, V., et al.. (2004). Cohomology of line bundles on Schubert varieties?I. Transformation Groups. 9(2). 7 indexed citations
14.
Saluja, Sanjeev, et al.. (2003). Descriptive complexity of Hash P functions. 38. 169–184.
15.
Shyamasundar, R. K., et al.. (2002). Multiprocessors scheduling for imprecise computations in a hard real-time environment. 24. 374–378. 4 indexed citations
16.
Halldórsson, Magnús M., Jaikumar Radhakrishnan, & K. V. Subrahmanyam. (2002). Directed vs. undirected monotone contact networks for threshold functions. 604–613. 4 indexed citations
17.
Subrahmanyam, K. V., et al.. (2000). Computing Mimicking Networks. Algorithmica. 26(1). 31–49.
18.
Ramos, Edgar A., et al.. (1997). Solving Some Discrepancy Problems in NC. Lecture notes in computer science. 29(3). 22–36. 3 indexed citations
19.
Saluja, Sanjeev, et al.. (1995). Descriptive Complexity of #P Functions. Journal of Computer and System Sciences. 50(3). 493–505. 24 indexed citations
20.
Radhakrishnan, Jaikumar & K. V. Subrahmanyam. (1994). Directed monotone contact networks for threshold functions. Information Processing Letters. 50(4). 199–203. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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